Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG)
- 1st Edition - January 16, 2022
- Latest edition
- Authors: Archana Bajirao Kanwade, Vinayak Bairagi
- Language: English
Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG) presents a new and innovative method of COPD diagnosis using EMG to analyze sternomas… Read more
Description
Description
Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG) presents a new and innovative method of COPD diagnosis using EMG to analyze sternomastoid muscle activity using features extraction and classification. The book describes the methodology of EMG analysis, the slope-based onset detection algorithm and SEMG analysis in time, frequency and time frequency domain analyses. It also explores the identification of frequencies for single frequency Continuous Wavelet Transform (CWT) analysis and feature extraction and selection for successful classification COPD into its severity grades.
The book provides a compilation of all techniques used in the literatures and emphasizes newly proposed techniques for the early detection of COPD. Fully comprehensive, the book includes discussion of limitations of existing methods for COPD diagnosis and introduces new efficient methods for COPD identification, classification and early diagnosis.
Key features
Key features
- Provides an easy, simple and comprehensive guide to using EMG analysis for COPD diagnosis
- Presents detailed explanations of the recently developed slope-based onset detection algorithm for muscle activity detection, along with numerous original figures, tables and graphs to aid interpretation
- Includes a complete review of various features, such as extraction using single frequency CWT analysis and the feature selection algorithm for COPD diagnosis
Readership
Readership
Researchers, academics and scientists working in the field of Respiratory diseases, Biomedical Engineering, EMG signal processing and Pulmonologists. Biomedical Signal Processing Course specifically for the EMG signal Processing details. Respiratory medicine branch for Chronic Obstructive Pulmonary Disease subject
Table of contents
Table of contents
1 INTRODUCTION
1.1 Chronic Obstructive Pulmonary Disease
1.2 Respiratory Mechanics
1.3 Electromyography
1.4 Motivation
1.5 Need of Research
2 METHODOLOGY
2.1 Introduction
2.2 Methodology
2.2.1 Sample Selection, Data Collection, and Experimental Setup
2.3 Recording Techniques
2.4 Skin Preparations
2.5 EMG Affecting Factors
2.6 EMG Noise
2.7 EMG analysis
2.7.1 Time domain analysis techniques
2.7.2 Frequency domain analysis techniques
2.7.3 Time-Frequency domain analysis techniques
2.8 Feature Selection and Classification
2.9 Summary
3 COPD AND HEALTHY CLASSIFICATION
3.1 Introduction
3.2 Methodology
3.3 Time Domain analysis
3.4 Onset Detection Algorithm
3.4.1 Improved Slope Based Onset Detection Algorithm
3.5 Results of Classification
3.5.1 Performance Evaluation
3.5.2 Feature Selection
3.5.3 Classification
3.6 Summary
4 COPD GRADE CLASSIFICATION
4.1 Introduction
4.2 Frequency Domain Analysis
4.2.1 Power Spectral Density analysis
4.2.2 Spectrum at window length of 15 samples
4.2.3 Spectrum analysis at onset and offset area
4.3 Time-Frequency Domain Analysis
4.3.1 Low-Frequency Region
4.3.2 High-Frequency Region
4.4 Feature Selection Algorithm
4.4.1 Presented Feature Selection Algorithm
4.4.2 Backward Elimination using Regression
4.4.3 Analysis of features using Weka tool
4.5 Results
5 EARLY DETECTION OF COPD
5.1 Introduction
5.2 Early Diagnosis Model
5.3 Results and Summary
6 RESULTS AND DISCUSSION
6.1 Introduction
6.2 Slope Based Onset Detection Algorithm
6.3 COPD and Healthy Classification
6.4 COPD Grade Classification
6.5 Summary
7 CONCLUSION
7.1 Conclusion
7.2 Research Contributions
7.3 Future Scope
Bibliography
Product details
Product details
- Edition: 1
- Latest edition
- Published: January 16, 2022
- Language: English
About the authors
About the authors
AK
Archana Bajirao Kanwade
VB